We implemented three baseline classifiers: character-level convolutional neural network (CharCNN) [1]}, bidirectional long short-term memory (BiLSTM) [2]}, and bidirectional encoder representations from Transformer (BERT) [3]} based model.
For BERT, we adopt KoBERThttps://github.com/SKTBrain/KoBERT, a pre-trained module for the Korean language, and apply its tokenizer to BiLSTM as well.
The detailed configurations are provided in Appendix , and we additionally report the term matching approach using the aforementioned profanity terms to compare with the benchmarks.
